Effects of lidar coverage and field plot data numerosity on forest growing stock volume estimation

Forest parameter estimation is required to support the sustainable management of forest ecosystems. Currently, forest resource assessment is increasingly linked to auxiliary information obtained from remote sensing (RS) technologies. In forest parameter estimation, airborne laser scanning (ALS) data...

Full description

Saved in:
Bibliographic Details
Published inEuropean journal of remote sensing Vol. 55; no. 1; pp. 199 - 212
Main Authors D'Amico, Giovanni, McRoberts, Ronald E., Giannetti, Francesca, Vangi, Elia, Francini, Saverio, Chirici, Gherardo
Format Journal Article
LanguageEnglish
Published Cagiari Taylor & Francis 31.12.2022
Taylor & Francis Ltd
Taylor & Francis Group
Subjects
Airborne laser scanning
Airborne lasers
Airborne sensing
Estimators
Forest ecosystems
Forest management
Forest resources
Forest surveys
Forests
growing stock volume
Landsat
landsat 7 ETM
Landsat satellites
Lidar
Mathematical models
National Forest Inventory
Parameter estimation
Remote sensing
Satellite imagery
Strategic management
Sustainability management
Online AccessGet full text
ISSN2279-7254
2279-7254
DOI10.1080/22797254.2022.2042397

Cover

Abstract Forest parameter estimation is required to support the sustainable management of forest ecosystems. Currently, forest resource assessment is increasingly linked to auxiliary information obtained from remote sensing (RS) technologies. In forest parameter estimation, airborne laser scanning (ALS) data have been demonstrated to be an invaluable source of information. However, ALS data are often not available for the entire forest area, whereas images from multiple satellite systems offer new opportunities for large-scale forest surveys. This study aims to assess and estimate the contribution of field plot data and ALS data along with Landsat data to the precision of growing stock volume (GSV) estimates. We compared different approaches for model-assisted estimation of mean forest GSV per unit area using different proportions of field sample data, ALS cover data, and wall-to-wall Landsat data. Model-assisted estimators were used with NFI sample data in an Italian study area using 10 RS predictors, specifically the seven Landsat 7 ETM+ bands and three fine-resolution metrics based on ALS-derived canopy height. We found that relative to the standard simple expansion estimator, the model-assisted estimators produced relative efficiency of 1.16 when using only Landsat data and relative efficiencies as great as 1.33 when using increasing levels of ALS coverage.
AbstractList Forest parameter estimation is required to support the sustainable management of forest ecosystems. Currently, forest resource assessment is increasingly linked to auxiliary information obtained from remote sensing (RS) technologies. In forest parameter estimation, airborne laser scanning (ALS) data have been demonstrated to be an invaluable source of information. However, ALS data are often not available for the entire forest area, whereas images from multiple satellite systems offer new opportunities for large-scale forest surveys. This study aims to assess and estimate the contribution of field plot data and ALS data along with Landsat data to the precision of growing stock volume (GSV) estimates. We compared different approaches for model-assisted estimation of mean forest GSV per unit area using different proportions of field sample data, ALS cover data, and wall-to-wall Landsat data. Model-assisted estimators were used with NFI sample data in an Italian study area using 10 RS predictors, specifically the seven Landsat 7 ETM+ bands and three fine-resolution metrics based on ALS-derived canopy height. We found that relative to the standard simple expansion estimator, the model-assisted estimators produced relative efficiency of 1.16 when using only Landsat data and relative efficiencies as great as 1.33 when using increasing levels of ALS coverage.
Author Giannetti, Francesca
Vangi, Elia
Chirici, Gherardo
McRoberts, Ronald E.
Francini, Saverio
D'Amico, Giovanni
Author_xml – sequence: 1
  givenname: Giovanni
  orcidid: 0000-0002-2341-3268
  surname: D'Amico
  fullname: D'Amico, Giovanni
  email: giovanni.damico@unifi.it
  organization: Environment and Forestry (Dagri), University of Florence
– sequence: 2
  givenname: Ronald E.
  surname: McRoberts
  fullname: McRoberts, Ronald E.
  organization: University of Minnesota
– sequence: 3
  givenname: Francesca
  orcidid: 0000-0002-4590-827X
  surname: Giannetti
  fullname: Giannetti, Francesca
  organization: Environment and Forestry (Dagri), University of Florence
– sequence: 4
  givenname: Elia
  orcidid: 0000-0002-9772-2258
  surname: Vangi
  fullname: Vangi, Elia
  organization: University of Molise
– sequence: 5
  givenname: Saverio
  orcidid: 0000-0001-6991-0289
  surname: Francini
  fullname: Francini, Saverio
  organization: Environment and Forestry (Dagri), University of Florence
– sequence: 6
  givenname: Gherardo
  orcidid: 0000-0002-0669-5726
  surname: Chirici
  fullname: Chirici, Gherardo
  organization: Environment and Forestry (Dagri), University of Florence
BookMark eNqFUUtrnCEUlZBC0iQ_oSB0PanP-ZRuWkLaBgLdNGu5vganjk79nIT593UyCZQuWhcq955zvMfzFp2WWgJC7yi5pkSRD4xNemJSXDPC2NgE43o6QeeH-uLQOP3jfoau5nlNxlKETEqfI3sbY3B9xjXinDw07OpjaLAKGIrHMYXs8TbXjj10wGW3Ca3Oqe9xLTjWFuaOV60-pbLCc6_uJ36seYDwaKQN9FTLJXoTIc_h6uW8QA9fbn_cfFvcf_96d_P5fuGEpH1hOQcHyjqhlJQiCL2US8FACFBUqugisTraqCfrtQDJvIzaaqes1YFSwS_Q3VHXV1ibbRvPt72pkMxzobaVgdaTy8Fw6qwFR8QESxG8VRbkEJWaaAaO86H1_qi1bfXXbngx67prZYxv2CS4onyp9UB9PKLc-JO5hWhc6s-ee4OUDSXmkJF5zcgcMjIvGQ22_Iv9OvP_eJ-OvFRGABt4qi1702Gfa4sNikvzMPhPid__w6sK
CitedBy_id crossref_primary_10_1093_forestry_cpad041
crossref_primary_10_1080_22797254_2024_2334717
crossref_primary_10_3390_s22052015
crossref_primary_10_36930_40350103
Cites_doi 10.1109/JSTARS.2012.2227299
10.1139/x98-166
10.1080/02827581.2017.1416666
10.1016/j.rse.2011.07.002
10.1016/J.JAG.2019.101959
10.1016/S0034-4257(01)00290-5
10.1139/cjfr-2014-0203
10.1109/TGRS.2010.2068574
10.3334/ORNLDAAC/1146
10.1016/j.rse.2017.09.036
10.3832/ifor3648-014
10.3390/rs8060469
10.1016/j.rse.2019.01.019
10.1080/01431160701736489
10.1016/j.foreco.2016.07.007
10.3390/rs10111832
10.1016/j.rse.2016.07.007
10.1016/j.rse.2019.02.015
10.1016/j.rse.2018.05.016
10.14214/sf.1567
10.1016/j.rse.2012.11.024
10.4060/ca9825en
10.1016/j.foreco.2014.07.025
10.1080/07038992.2014.945827
10.1016/j.rse.2006.03.003
10.1016/j.rse.2021.112307
10.1093/forestry/cpw041
10.1016/j.rse.2016.10.022
10.1016/j.rse.2017.03.026
10.1016/j.rse.2005.01.010
10.1080/02827580410019553
10.1016/j.rse.2015.11.012
10.1016/j.jag.2012.10.002
10.1007/s13595-016-0590-1
10.5558/tfc84807-6
10.1186/s40663-020-00277-6
10.1016/j.rse.2016.07.027
10.1016/j.rse.2015.11.010
10.1016/j.rse.2019.04.006
10.1080/07038992.2016.1207484
10.1080/22797254.2020.1806734
10.1080/01431161.2021.1899334
10.1016/j.rse.2017.06.031
10.1016/S0034-4257(01)00330-3
10.3390/rs11161906
10.1016/j.jag.2017.11.013
10.1080/17538947.2014.990526
10.1016/j.rse.2017.10.007
10.1139/cjfr-2015-0077
10.3390/rs9080766
10.1155/2012/436537
10.1007/978-1-4612-4378-6
10.1016/j.rse.2017.04.004
ContentType Journal Article
Copyright 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 2022
2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 2022
– notice: 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID 0YH
AAYXX
CITATION
3V.
7TG
7XB
8FD
8FK
8G5
ABUWG
AEUYN
AFKRA
AZQEC
BENPR
CCPQU
DWQXO
GNUQQ
GUQSH
H8D
KL.
L7M
M2O
MBDVC
PHGZM
PHGZT
PIMPY
PKEHL
PQEST
PQQKQ
PQUKI
PRINS
Q9U
DOA
DOI 10.1080/22797254.2022.2042397
DatabaseName Taylor & Francis Open Access
CrossRef
ProQuest Central (Corporate)
Meteorological & Geoastrophysical Abstracts
ProQuest Central (purchase pre-March 2016)
Technology Research Database
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Research Library
ProQuest Central (Alumni)
ProQuest One Sustainability
ProQuest Central
ProQuest Central Essentials
ProQuest Central
ProQuest One
ProQuest Central
ProQuest Central Student
ProQuest Research Library
Aerospace Database
Meteorological & Geoastrophysical Abstracts - Academic
Advanced Technologies Database with Aerospace
Research Library
Research Library (Corporate)
ProQuest Central Premium
ProQuest One Academic
ProQuest Publicly Available Content Database
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
ProQuest Central Basic
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
Publicly Available Content Database
Research Library Prep
ProQuest Central Student
Technology Research Database
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
ProQuest Central (Alumni Edition)
ProQuest One Community College
Research Library (Alumni Edition)
ProQuest Central China
ProQuest Central
Aerospace Database
ProQuest One Sustainability
Meteorological & Geoastrophysical Abstracts
ProQuest Central Korea
ProQuest Research Library
ProQuest Central (New)
Advanced Technologies Database with Aerospace
ProQuest Central Basic
ProQuest One Academic Eastern Edition
ProQuest One Academic UKI Edition
ProQuest One Academic
Meteorological & Geoastrophysical Abstracts - Academic
ProQuest One Academic (New)
ProQuest Central (Alumni)
DatabaseTitleList
Publicly Available Content Database
Database_xml – sequence: 1
  dbid: DOA
  name: Directory of Open Access Journals (DOAJ)
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: 0YH
  name: Taylor & Francis Open Access
  url: https://www.tandfonline.com
  sourceTypes: Publisher
– sequence: 3
  dbid: BENPR
  name: ProQuest Central
  url: http://www.proquest.com/pqcentral?accountid=15518
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Geography
EISSN 2279-7254
EndPage 212
ExternalDocumentID oai_doaj_org_article_31cbbac047a64edb8ba5d9459092ac33
10_1080_22797254_2022_2042397
2042397
Genre Research Article
GroupedDBID .4S
0YH
5VS
8G5
AAHBH
ABUWG
ACGFS
ADBBV
ADMLS
AEGXH
AENEX
AEUYN
AFKRA
ALMA_UNASSIGNED_HOLDINGS
ARCSS
AZQEC
BCNDV
BENPR
BPHCQ
CCPQU
DWQXO
EBS
GNUQQ
GROUPED_DOAJ
GUQSH
H13
KQ8
M2O
M4Z
M~E
PHGZT
PIMPY
PQQKQ
PROAC
RNS
TDBHL
TFW
TUS
AAYXX
CITATION
PHGZM
3V.
7TG
7XB
8FD
8FK
H8D
KL.
L7M
MBDVC
PKEHL
PQEST
PQUKI
PRINS
Q9U
PUEGO
ID FETCH-LOGICAL-c451t-b33aca8bc488554e4965642a44a8158fcf0b9fbf97bd94a52d5f9b9c8bb9e1143
IEDL.DBID BENPR
ISSN 2279-7254
IngestDate Wed Aug 27 01:16:38 EDT 2025
Mon Jun 30 12:23:03 EDT 2025
Tue Jul 01 05:25:59 EDT 2025
Thu Apr 24 23:08:09 EDT 2025
Thu Apr 03 03:04:00 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 1
Language English
License open-access: http://creativecommons.org/licenses/by/4.0/: http://creativecommons.org/licenses/by/4.0/: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c451t-b33aca8bc488554e4965642a44a8158fcf0b9fbf97bd94a52d5f9b9c8bb9e1143
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0002-0669-5726
0000-0002-4590-827X
0000-0001-6991-0289
0000-0002-2341-3268
0000-0002-9772-2258
OpenAccessLink https://www.proquest.com/docview/2743813699?pq-origsite=%requestingapplication%&accountid=15518
PQID 2743813699
PQPubID 3933194
PageCount 14
ParticipantIDs proquest_journals_2743813699
crossref_citationtrail_10_1080_22797254_2022_2042397
doaj_primary_oai_doaj_org_article_31cbbac047a64edb8ba5d9459092ac33
crossref_primary_10_1080_22797254_2022_2042397
informaworld_taylorfrancis_310_1080_22797254_2022_2042397
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2022-12-31
PublicationDateYYYYMMDD 2022-12-31
PublicationDate_xml – month: 12
  year: 2022
  text: 2022-12-31
  day: 31
PublicationDecade 2020
PublicationPlace Cagiari
PublicationPlace_xml – name: Cagiari
PublicationTitle European journal of remote sensing
PublicationYear 2022
Publisher Taylor & Francis
Taylor & Francis Ltd
Taylor & Francis Group
Publisher_xml – name: Taylor & Francis
– name: Taylor & Francis Ltd
– name: Taylor & Francis Group
References e_1_3_2_28_1
e_1_3_2_49_1
e_1_3_2_20_1
e_1_3_2_41_1
e_1_3_2_43_1
e_1_3_2_24_1
e_1_3_2_45_1
e_1_3_2_26_1
e_1_3_2_47_1
e_1_3_2_62_1
e_1_3_2_60_1
e_1_3_2_16_1
e_1_3_2_39_1
e_1_3_2_9_1
e_1_3_2_18_1
e_1_3_2_7_1
e_1_3_2_31_1
e_1_3_2_10_1
e_1_3_2_33_1
e_1_3_2_52_1
e_1_3_2_12_1
e_1_3_2_35_1
e_1_3_2_58_1
e_1_3_2_14_1
e_1_3_2_37_1
e_1_3_2_56_1
e_1_3_2_3_1
e_1_3_2_50_1
e_1_3_2_27_1
e_1_3_2_29_1
e_1_3_2_42_1
e_1_3_2_21_1
e_1_3_2_44_1
e_1_3_2_23_1
e_1_3_2_46_1
e_1_3_2_25_1
e_1_3_2_48_1
e_1_3_2_61_1
e_1_3_2_40_1
Tabacchi G. (e_1_3_2_53_1) 2007
e_1_3_2_17_1
e_1_3_2_38_1
e_1_3_2_8_1
e_1_3_2_19_1
e_1_3_2_2_1
e_1_3_2_30_1
e_1_3_2_55_1
e_1_3_2_11_1
e_1_3_2_32_1
e_1_3_2_6_1
e_1_3_2_13_1
e_1_3_2_34_1
e_1_3_2_59_1
e_1_3_2_4_1
INFC (e_1_3_2_22_1) 2004
e_1_3_2_15_1
e_1_3_2_36_1
e_1_3_2_57_1
Tabacchi G. (e_1_3_2_54_1) 2011
e_1_3_2_51_1
Cochran W. G. (e_1_3_2_5_1) 1977
References_xml – ident: e_1_3_2_8_1
– ident: e_1_3_2_37_1
  doi: 10.1109/JSTARS.2012.2227299
– ident: e_1_3_2_17_1
  doi: 10.1139/x98-166
– ident: e_1_3_2_24_1
  doi: 10.1080/02827581.2017.1416666
– ident: e_1_3_2_36_1
  doi: 10.1016/j.rse.2011.07.002
– ident: e_1_3_2_3_1
  doi: 10.1016/J.JAG.2019.101959
– ident: e_1_3_2_43_1
  doi: 10.1016/S0034-4257(01)00290-5
– ident: e_1_3_2_6_1
  doi: 10.1139/cjfr-2014-0203
– ident: e_1_3_2_19_1
– start-page: 36
  year: 2004
  ident: e_1_3_2_22_1
  article-title: Il disegno di campionamento. Inventario Nazionale delle Foreste e dei Serbatoi Forestali di Carbonio. MiPAF - Direzione Generale per le Risorse Forestali Montane e Idriche, Corpo Forestale dello Stato
  publication-title: ISAFA, Trento
– ident: e_1_3_2_45_1
  doi: 10.1109/TGRS.2010.2068574
– ident: e_1_3_2_31_1
  doi: 10.3334/ORNLDAAC/1146
– ident: e_1_3_2_33_1
  doi: 10.1016/j.rse.2017.09.036
– ident: e_1_3_2_7_1
  doi: 10.3832/ifor3648-014
– ident: e_1_3_2_62_1
  doi: 10.3390/rs8060469
– ident: e_1_3_2_2_1
  doi: 10.1016/j.rse.2019.01.019
– ident: e_1_3_2_21_1
  doi: 10.1080/01431160701736489
– volume-title: Sampling techniques
  year: 1977
  ident: e_1_3_2_5_1
– ident: e_1_3_2_32_1
  doi: 10.1016/j.foreco.2016.07.007
– start-page: 413
  volume-title: Inventario Nazionale delle Foreste e dei Serbatoi Forestali di Carbonio
  year: 2007
  ident: e_1_3_2_53_1
– ident: e_1_3_2_50_1
  doi: 10.3390/rs10111832
– ident: e_1_3_2_34_1
  doi: 10.1016/j.rse.2016.07.007
– ident: e_1_3_2_60_1
  doi: 10.1016/j.rse.2019.02.015
– ident: e_1_3_2_14_1
  doi: 10.1016/j.rse.2018.05.016
– ident: e_1_3_2_25_1
  doi: 10.14214/sf.1567
– ident: e_1_3_2_23_1
  doi: 10.1016/j.rse.2012.11.024
– ident: e_1_3_2_9_1
  doi: 10.4060/ca9825en
– ident: e_1_3_2_35_1
  doi: 10.1016/j.foreco.2014.07.025
– start-page: 415
  volume-title: Stima del volume e della fitomassa delle principali specie forestali italiene, Equazioni di previsione, tavole del volume e tavole della fitomassa arborea epigea
  year: 2011
  ident: e_1_3_2_54_1
– ident: e_1_3_2_58_1
  doi: 10.1080/07038992.2014.945827
– ident: e_1_3_2_15_1
  doi: 10.1016/j.rse.2006.03.003
– ident: e_1_3_2_61_1
  doi: 10.1016/j.rse.2021.112307
– ident: e_1_3_2_39_1
– ident: e_1_3_2_41_1
  doi: 10.1093/forestry/cpw041
– ident: e_1_3_2_46_1
  doi: 10.1016/j.rse.2016.10.022
– ident: e_1_3_2_10_1
  doi: 10.1016/j.rse.2017.03.026
– ident: e_1_3_2_26_1
  doi: 10.1016/j.rse.2005.01.010
– ident: e_1_3_2_44_1
  doi: 10.1080/02827580410019553
– ident: e_1_3_2_18_1
  doi: 10.1016/j.rse.2015.11.012
– ident: e_1_3_2_40_1
  doi: 10.1016/j.jag.2012.10.002
– ident: e_1_3_2_49_1
  doi: 10.1007/s13595-016-0590-1
– ident: e_1_3_2_59_1
  doi: 10.5558/tfc84807-6
– ident: e_1_3_2_28_1
  doi: 10.1186/s40663-020-00277-6
– ident: e_1_3_2_47_1
  doi: 10.1016/j.rse.2016.07.027
– ident: e_1_3_2_4_1
  doi: 10.1016/j.rse.2015.11.010
– ident: e_1_3_2_55_1
  doi: 10.1016/j.rse.2019.04.006
– ident: e_1_3_2_57_1
  doi: 10.1080/07038992.2016.1207484
– ident: e_1_3_2_13_1
  doi: 10.1080/22797254.2020.1806734
– ident: e_1_3_2_12_1
  doi: 10.1080/01431161.2021.1899334
– ident: e_1_3_2_16_1
  doi: 10.1016/j.rse.2017.06.031
– ident: e_1_3_2_38_1
  doi: 10.1016/S0034-4257(01)00330-3
– ident: e_1_3_2_27_1
  doi: 10.3390/rs11161906
– ident: e_1_3_2_42_1
  doi: 10.1016/j.jag.2017.11.013
– ident: e_1_3_2_29_1
  doi: 10.1080/17538947.2014.990526
– ident: e_1_3_2_48_1
  doi: 10.1016/j.rse.2017.10.007
– ident: e_1_3_2_51_1
  doi: 10.1139/cjfr-2015-0077
– ident: e_1_3_2_56_1
  doi: 10.3390/rs9080766
– ident: e_1_3_2_11_1
– ident: e_1_3_2_30_1
  doi: 10.1155/2012/436537
– ident: e_1_3_2_52_1
  doi: 10.1007/978-1-4612-4378-6
– ident: e_1_3_2_20_1
  doi: 10.1016/j.rse.2017.04.004
SSID ssj0000800789
Score 2.29007
Snippet Forest parameter estimation is required to support the sustainable management of forest ecosystems. Currently, forest resource assessment is increasingly...
SourceID doaj
proquest
crossref
informaworld
SourceType Open Website
Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 199
SubjectTerms Airborne laser scanning
Airborne lasers
Airborne sensing
Estimators
Forest ecosystems
Forest management
Forest resources
Forest surveys
Forests
growing stock volume
Landsat
landsat 7 ETM
Landsat satellites
Lidar
Mathematical models
National Forest Inventory
Parameter estimation
Remote sensing
Satellite imagery
Strategic management
Sustainability management
SummonAdditionalLinks – databaseName: DOAJ Directory of Open Access Journals
  dbid: DOA
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrZ3NTx0hEMBJ46W9GFvb-Kw1HLxuZR-wwLFtakyTetLEG2EGUNuXfUbXg_99-XrmVRO9eN0sYTIMMENmfkPIgYgyRKF4h5G7TrjQd3pA6JgHhkINGAqn4PfJcHwmfp3L87VWXzknrOKBq-IOeY8ADplQbhDBgwYnvRHSMDN3yAvnkxm2Fkz9aX6Q0mZVsqPZYSblqXl5RpnnAqwMvlP_XUaF2f-IWPrkhC7XztEW2Wz-Iv1W5XxP3oTxA3nbWpdf3m8TqPzhW7qMdHHl3Q3FnJWZjgnqRk9Lhhq9XiwnmpNB6ZjrLXOi1j1djjSJkOakFykWT1cYTY4g_qX1wKIZv1HrGj-Ss6Ofpz-Ou9Y4oUMh-6kDzh06DZh2Z3IXQmbCpzjDCeF0L3XEyMBEiEZBUqWTcy-jAYMawIQUIPFPZGNcjmGHUAOeYfDR94oJUArCILGPUnvkwgQ1I2KlQYuNKp6bWyxs3-CjK8XbrHjbFD8jXx-GXVesxksDvuflefg5U7HLh2QrttmKfclWZsSsL66dyqNIrB1M0ujnBdhbWYJt2_zWppA-eTx8MGb3NeT7TN7lKStHco9sTDd34UvyeSbYL-b9Dw94_AM
  priority: 102
  providerName: Directory of Open Access Journals
– databaseName: Taylor & Francis Open Access
  dbid: 0YH
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwELagHOBS8RQLBfnANZDEdhwfC2q1QoITleBkecZ2QaySajc99N8zdpxVC6IcOCbKOPbY87JmvmHsjYwqRKlFhVG4SrrQVH2HUNUeapS6w5BxCj597tZn8uNXtWQT7kpaZYqh4wwUkXV1Em4HuyUj7l0CvdNtvhFpUy1VwrDTd9m9VpO9oSNdf1vvr1mSQ6R7s9Tu_I36hlXK4P2_QZf-oaqz_Tl9yA6L48iP551-xO6E4TG7X3qYf796wmAGIt7xMfLND--2HFN6JukLTivlOVWNX2zGiaesUD6kwsuUsXXFx4HTFOif_JyCcrJlnDxC_MlnzcUTDsdc4PiUnZ2efPmwrkoHhQqlaqYKhHDoekASU_IbQgKHp4DDSen6RvURYw0mQjQavJFOtV5FAwZ7ABMoUhLP2MEwDuE54wZ8jcFH3-hagtYQOoVNVL1HIU3QKyYXDlos8OKpy8XGNgWFdGG8TYy3hfEr9nZPdjHja_yL4H3anv3HCR47vxi357ZImxUNAjispXadDB56cIoWqExtWodCrJi5vrl2yrcjcW5lQtS3T-BoOQm2yPvOUmxPro_ojHnxH0O_ZA_S44wjecQOpu1leEU-zwSv86n-BQq7-CQ
  priority: 102
  providerName: Taylor & Francis
Title Effects of lidar coverage and field plot data numerosity on forest growing stock volume estimation
URI https://www.tandfonline.com/doi/abs/10.1080/22797254.2022.2042397
https://www.proquest.com/docview/2743813699
https://doaj.org/article/31cbbac047a64edb8ba5d9459092ac33
Volume 55
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwhV1LT9wwELZgObSXqk91C6x86DXFWdtxfECoINCqUldVVSR6ijx-0IpVsl3SA_8ej-NsXxK9JnEeY3temfk-Qt6KIH0Qihc2cFMI48uiriwUzAGzQlXWJ5yCj8tqcSk-XMmrHbIce2GwrHLUiUlRu85ijvwoRk_RuPBK65P1jwJZo_Dv6kihYTK1gjtOEGO7ZC-qZMkmZO_0fPnp8zbrgv6RqvXYylOzI0TQU_OUXpljYxYC4qk_jFTC8v8LyfQfzZ3M0cVT8iT7kfT9MPHPyI5vn5NHmdL8290LAgMu8S3tAl19d2ZDLVZrRvVBTetoqlyj61XXUywSpS32YWIB1x3tWhpfIT6TXscYPZo2Gh1Ee0MHRUYRlmPod3xJLi_Ov5wtikyoUFghy74Azo01Ndi4a6Mb4RErPsYfRghTl7IONjDQAYJW4LQwcu5k0KBtDaB9DJz4KzJpu9a_JlSDY9a74ErFBCgFvpK2DLJ2lgvt1ZSIUYKNzWjjSHqxasoMSjoKvkHBN1nwU_JuO2w9wG38b8ApTs_2YkTLTge6zXWTN1_DSwtgLBPKVMI7qMHI-IFSMz03lvMp0b9PbtOnZEkYmE3i6Idf4GBcCU3e_rfNr8X65uHT--Qx3mxAjjwgk37z0x9GL6eHGdllXxezvIBnKVdwD_xI-08
linkProvider ProQuest
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELbK9lAuiKdYKOADHEOT2I7tQ4UotNrSdoVQK_Vm_GwRq2TZDar2z_Hb8CTO8pLKqdckdpyxPTOezHwfQi9pYD5QTjIbiM6o9kUmKmuy3JncUl5Z3-EUnEyryRn9cM7ON9CPoRYG0ioHndgpatdYiJHvxNNTNC6kkvLN_FsGrFHwd3Wg0NCJWsHtdhBjqbDjyK-u4hFuuXv4Ps73q7I82D99N8kSy0BmKSvazBCirRbGxqUcbasHAPXolGtKtSiYCDbkRgYTJDdOUs1Kx4I00gpjpI-nCRL7vYU2KQRQRmhzb3_68dM6ygP-GBdyKB0S-Q4g9vGyC-eUUAgGAHz8D6PYcQf8hZz6j6XozN_BXXQn-a34bb_Q7qENX99HW4lC_XL1AJkeB3mJm4BnX5xeYAvZoVFdYV073GXK4fmsaTEkpeIa6j4hYWyFmxrHIcR34otFcxVNKY4Oqf2Ke8WJAQakr698iM5uRLSP0Khuav8YYWlcbr0LruA5NZwbXzFbBCacJVR6PkZ0kKCyCd0cSDZmqkggqIPgFQheJcGP0et1s3kP7_G_BnswPeuHAZ27u9AsLlTa7IoU1hhtc8p1Rb0zwmgWP5DJXJbaEjJG8vfJVW0XnAk9k0psff0AtoeVoJK6Wapfm-PJ9bdfoK3J6cmxOj6cHj1Ft6HjHrVyG43axXf_LHpYrXmeljFGn2965_wEy7w3FA
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwELagSMAFlZfY0oIPXAPJ2o7tI9CullfFgUpwsjxju0WsktVueui_x3acFQ8BB65JJonHnvE31sw3hDzjQfjAJaswMFtx65tKtQhV7aBGLlv0mafgw2m7PONvP4spm3Bb0ipTDB1Goojsq5Nxr12YMuJeJNI7Oc8nIvNUS5U47OR1ckOoCM_jkq6_LHfHLAkQSaWn2p0_Sf-0K2Xy_l-oS39z1Xn_WeyTOwU40pfjTN8l13x3j9wqPcwvru4TGImIt7QPdPXV2Q3FlJ4Z_QWNI6U5VY2uV_1AU1Yo7VLhZcrYuqJ9R-MvxG_S8xiUx72MRkSI3-jouWji4RgLHB-Qs8XJp9fLqnRQqJCLZqiAMYtWAUYzjbjBJ3L4GHBYzq1qhAoYatABgpbgNLdi7kTQoFEBaB8jJfaQ7HV95x8RqsHV6F1wjaw5SAm-FdgEoRwyrr2cET5p0GChF09dLlamKSykk-JNUrwpip-R5zux9civ8S-BV2l6dg8neux8od-cm2JthjUIYLHm0rbcO1BgRRyg0LWeW2RsRvSPk2uGfDoSxlYmUfrvP3A4rQRT7H1rYmwfoQ9rtT74j1c_JTc_Hi_M-zen7x6T2-nOSCl5SPaGzaU_ivBngCd5gX8H_Tn6wg
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Effects+of+lidar+coverage+and+field+plot+data+numerosity+on+forest+growing+stock+volume+estimation&rft.jtitle=European+journal+of+remote+sensing&rft.au=D%E2%80%99Amico%2C+Giovanni&rft.au=McRoberts%2C+Ronald+E.&rft.au=Giannetti%2C+Francesca&rft.au=Vangi%2C+Elia&rft.date=2022-12-31&rft.issn=2279-7254&rft.eissn=2279-7254&rft.volume=55&rft.issue=1&rft.spage=199&rft.epage=212&rft_id=info:doi/10.1080%2F22797254.2022.2042397&rft.externalDBID=n%2Fa&rft.externalDocID=10_1080_22797254_2022_2042397
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2279-7254&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2279-7254&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2279-7254&client=summon